- The Most In Demand Skills for Data Engineers in 2021 - May 18, 2021.
If you are preparing to make a career in data or are looking for opportunities to skill-up in your current data-centric role, then this analysis of in-demand skills for 2021, based on over 17,000 Data Engineer job postings, should offer you a good idea as to which programming languages and software tools are increasing and decreasing in importance.
Apache Spark, AWS, Data Engineer, Data Science Skills, Data Scientist, Python, Skills, SQL
- Easy MLOps with PyCaret + MLflow - May 18, 2021.
A beginner-friendly, step-by-step tutorial on integrating MLOps in your Machine Learning experiments using PyCaret.
Machine Learning, MLflow, MLOps, PyCaret, Python
- Best Python Books for Beginners and Advanced Programmers - May 14, 2021.
Let's take a look at nine of the best Python books for both beginners and advanced programmers, covering topics such as data science, machine learning, deep learning, NLP, and more.
Analytics, Books, Data Science, Deep Learning, Machine Learning, Python
- Super Charge Python with Pandas on GPUs Using Saturn Cloud - May 12, 2021.
Saturn Cloud is a tool that allows you to have 10 hours of free GPU computing and 3 hours of Dask Cluster computing a month for free. In this tutorial, you will learn how to use these free resources to process data using Pandas on a GPU. The experiments show that Pandas is over 1,000,000% slower on a CPU as compared to running Pandas on a Dask cluster of GPUs.
Cloud, GPU, Pandas, Python
Essential Linear Algebra for Data Science and Machine Learning - May 10, 2021.
Linear algebra is foundational in data science and machine learning. Beginners starting out along their learning journey in data science--as well as established practitioners--must develop a strong familiarity with the essential concepts in linear algebra.
Data Science Education, Data Visualization, Linear Algebra, Linear Regression, Mathematics, Python
- Ensemble Methods Explained in Plain English: Bagging - May 10, 2021.
Understand the intuition behind bagging with examples in Python.
Algorithms, Bagging, Ensemble Methods, Python
Applying Python’s Explode Function to Pandas DataFrames - May 7, 2021.
Read this applied Python method to solve the issue of accessing column by date/ year using the Pandas library and functions lambda(), list(), map() & explode().
Data Analysis, Pandas, Programming, Python
- A Comprehensive Guide to Ensemble Learning – Exactly What You Need to Know - May 6, 2021.
This article covers ensemble learning methods, and exactly what you need to know in order to understand and implement them.
CatBoost, Ensemble Methods, Machine Learning, Python, random forests algorithm, scikit-learn, XGBoost
- Rebuilding My 7 Python Projects - May 5, 2021.
This is how I rebuilt My Python Projects: Data Science, Web Development & Android Apps.
Data Science, Programming, Project, Python
- How To Generate Meaningful Sentences Using a T5 Transformer - May 3, 2021.
Read this article to see how to develop a text generation API using the T5 transformer.
API, Hugging Face, Natural Language Generation, NLP, Python, Transformer
- XGBoost Explained: DIY XGBoost Library in Less Than 200 Lines of Python - May 3, 2021.
Understand how XGBoost work with a simple 200 lines codes that implement gradient boosting for decision trees.
Algorithms, Machine Learning, Python, XGBoost
- Gradient Boosted Decision Trees – A Conceptual Explanation - Apr 30, 2021.
Gradient boosted decision trees involves implementing several models and aggregating their results. These boosted models have become popular thanks to their performance in machine learning competitions on Kaggle. In this article, we’ll see what gradient boosted decision trees are all about.
CatBoost, Decision Trees, Gradient Boosting, Machine Learning, Python, scikit-learn, XGBoost
- Feature Engineering of DateTime Variables for Data Science, Machine Learning - Apr 29, 2021.
Learn how to make more meaningful features from DateTime type variables to be used by Machine Learning Models.
Data Science, Feature Engineering, Machine Learning, Python
- Multiple Time Series Forecasting with PyCaret - Apr 27, 2021.
A step-by-step tutorial to forecast multiple time series with PyCaret.
Forecasting, Machine Learning, PyCaret, Python, Time Series
- Production-Ready Machine Learning NLP API with FastAPI and spaCy - Apr 21, 2021.
Learn how to implement an API based on FastAPI and spaCy for Named Entity Recognition (NER), and see why the author used FastAPI to quickly build a fast and robust machine learning API.
API, FastAPI, NLP, Production, Python, spaCy
- Time Series Forecasting with PyCaret Regression Module - Apr 21, 2021.
PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. See how to use PyCaret's Regression Module for Time Series Forecasting.
Machine Learning, PyCaret, Python, Regression, Time Series
- Data Analysis Using Tableau - Apr 20, 2021.
Read this overview of using Tableau for sale data analysis, and see how visualization can help tell the business story.
Business, Data Analysis, Ecommerce, Python, Sales, Tableau
The Most In-Demand Skills for Data Scientists in 2021 - Apr 15, 2021.
If you are preparing to make a career as a Data Scientist or are looking for opportunities to skill-up in your current role, this analysis of in-demand skills for 2021, based on over 15,000 Data Scientist job postings, should offer you a good idea as to which programming languages and software tools are increasing and decreasing in importance.
AWS, Data Science Skills, Python, PyTorch, R, scikit-learn, SQL, TensorFlow
- How to Apply Transformers to Any Length of Text - Apr 12, 2021.
Read on to find how to restore the power of NLP for long sequences.
BERT, NLP, Python, Text Analytics, Transformer
- E-commerce Data Analysis for Sales Strategy Using Python - Apr 7, 2021.
Check out this informative and concise case study applying data analysis using Python to a well-defined e-commerce scenario.
Business, Data Analysis, Ecommerce, Python, Sales
- Automated Text Classification with EvalML - Apr 6, 2021.
Learn how EvalML leverages Woodwork, Featuretools and the nlp-primitives library to process text data and create a machine learning model that can detect spam text messages.
Automated Machine Learning, AutoML, NLP, Python, Text Analytics, Text Classification
Shapash: Making Machine Learning Models Understandable - Apr 2, 2021.
Establishing an expectation for trust around AI technologies may soon become one of the most important skills provided by Data Scientists. Significant research investments are underway in this area, and new tools are being developed, such as Shapash, an open-source Python library that helps Data Scientists make machine learning models more transparent and understandable.
Explainability, Machine Learning, Python, SHAP
- Easy AutoML in Python - Apr 1, 2021.
We’re excited to announce that a new open-source project has joined the Alteryx open-source ecosystem. EvalML is a library for automated machine learning (AutoML) and model understanding, written in Python.
Automated Machine Learning, AutoML, Machine Learning, Open Source, Python
- Software Engineering Best Practices for Data Scientists - Mar 30, 2021.
This is a crash course on how to bridge the gap between data science and software engineering.
Data Science, Data Scientist, Programming, Python, Software Engineering
- Data Science Curriculum for Professionals - Mar 25, 2021.
If you are looking to expand or transition your current professional career that is buried in spreadsheet analysis into one powered by data science, then you are in for an exciting but complex journey with much to explore and master. To begin your adventure, following this complete road map to guide you from a gnome in the forest of spreadsheets to an AI wizard known far and wide throughout the kingdom.
Cloud Computing, Data Science Education, Data Visualization, Machine Learning, Python, R, Roadmap, Statistics
Top 10 Python Libraries Data Scientists should know in 2021 - Mar 24, 2021.
So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.
Data Science, Keras, numpy, Pandas, Python, scikit-learn, Seaborn, TensorFlow
The Best Machine Learning Frameworks & Extensions for Scikit-learn - Mar 22, 2021.
Learn how to use a selection of packages to extend the functionality of Scikit-learn estimators.
Machine Learning, Python, scikit-learn
- How to build a DAG Factory on Airflow - Mar 19, 2021.
A guide to building efficient DAGs with half of the code.
Data Engineering, Data Workflow, Graphs, Python, Workflow
- A Simple Way to Time Code in Python - Mar 18, 2021.
Read on to find out how to use a decorator to time your functions.
Optimization, Programming, Python
- How to Begin Your NLP Journey - Mar 17, 2021.
In this blog post, learn how to process text using Python.
NLP, Python, Text Analytics
- Natural Language Processing Pipelines, Explained - Mar 16, 2021.
This article presents a beginner's view of NLP, as well as an explanation of how a typical NLP pipeline might look.
Explained, NLP, NLTK, Python, Text Analytics
- Kedro-Airflow: Orchestrating Kedro Pipelines with Airflow - Mar 12, 2021.
The Kedro team and Astronomer have released Kedro-Airflow 0.4.0 to help you develop modular, maintainable & reproducible code with orchestration superpowers!
Data Science, Interview, Pipeline, Python, Workflow
Know your data much faster with the new Sweetviz Python library - Mar 12, 2021.
One of the latest exploratory data analysis libraries is a new open-source Python library called Sweetviz, for just the purposes of finding out data types, missing information, distribution of values, correlations, etc. Find out more about the library and how to use it here.
Data Analysis, Data Exploration, Data Visualization, Python
- How to Speed Up Pandas with Modin - Mar 10, 2021.
The Modin library has the ability to scale your pandas workflows by changing one line of code and integration with the Python ecosystem and Ray clusters. This tutorial goes over how to get started with Modin and how it can speed up your pandas workflows.
Data Science, Distributed Systems, Modin, Pandas, Python, Workflow
- 4 Machine Learning Concepts I Wish I Knew When I Built My First Model - Mar 9, 2021.
Diving into building your first machine learning model will be an adventure -- one in which you will learn many important lessons the hard way. However, by following these four tips, your first and subsequent models will be put on a path toward excellence.
Feature Selection, Gradio, Hyperparameter, Machine Learning, Metrics, Python
- Beautiful decision tree visualizations with dtreeviz - Mar 8, 2021.
Improve the old way of plotting the decision trees and never go back!
Algorithms, Data Visualization, Decision Trees, Python
- 11 Essential Code Blocks for Complete EDA (Exploratory Data Analysis) - Mar 5, 2021.
This article is a practical guide to exploring any data science project and gain valuable insights.
Data Analysis, Data Exploration, Data Visualization, Pandas, Python
- Bayesian Hyperparameter Optimization with tune-sklearn in PyCaret - Mar 5, 2021.
PyCaret, a low code Python ML library, offers several ways to tune the hyper-parameters of a created model. In this post, I'd like to show how Ray Tune is integrated with PyCaret, and how easy it is to leverage its algorithms and distributed computing to achieve results superior to default random search method.
Bayesian, Hyperparameter, Machine Learning, Optimization, PyCaret, Python, scikit-learn
- 15 common mistakes data scientists make in Python (and how to fix them) - Mar 3, 2021.
Writing Python code that works for your data science project and performs the task you expect is one thing. Ensuring your code is readable by others (including your future self), reproducible, and efficient are entirely different challenges that can be addressed by minimizing common bad practices in your development.
Best Practices, Data Scientist, Jupyter, Mistakes, Programming, Python
- Getting Started with Distributed Machine Learning with PyTorch and Ray - Mar 3, 2021.
Ray is a popular framework for distributed Python that can be paired with PyTorch to rapidly scale machine learning applications.
Distributed Systems, Machine Learning, Python, PyTorch
- Speech to Text with Wav2Vec 2.0 - Mar 2, 2021.
Facebook recently introduced and open-sourced their new framework for self-supervised learning of representations from raw audio data called Wav2Vec 2.0. Learn more about it and how to use it here.
Hugging Face, NLP, Python, PyTorch, Transformer
- Are You Still Using Pandas to Process Big Data in 2021? Here are two better options - Mar 1, 2021.
When its time to handle a lot of data -- so much that you are in the realm of Big Data -- what tools can you use to wrangle the data, especially in a notebook environment? Pandas doesn’t handle really Big Data very well, but two other libraries do. So, which one is better and faster?
Big Data, Dask, Data Preparation, Pandas, Python, Vaex
Data Science Learning Roadmap for 2021 - Feb 26, 2021.
Venturing into the world of Data Science is an exciting, interesting, and rewarding path to consider. There is a great deal to master, and this self-learning recommendation plan will guide you toward establishing a solid understanding of all that is foundational to data science as well as a solid portfolio to showcase your developed expertise.
Data Engineering, Data Preparation, Data Science, Data Science Education, Python, Roadmap, SQL
- Pandas Profiling: One-Line Magical Code for EDA - Feb 24, 2021.
EDA can be automated using a Python library called Pandas Profiling. Let’s explore Pandas profiling to do EDA in a very short time and with just a single line code.
Data Analysis, Data Exploration, Data Science, Pandas, Python
- Powerful Exploratory Data Analysis in just two lines of code - Feb 22, 2021.
EDA is a fundamental early process for any Data Science investigation. Typical approaches for visualization and exploration are powerful, but can be cumbersome for getting to the heart of your data. Now, you can get to know your data much faster with only a few lines of code... and it might even be fun!
Data Analysis, Data Exploration, Data Visualization, Python
- Multidimensional multi-sensor time-series data analysis framework - Feb 19, 2021.
This blog post provides an overview of the package “msda” useful for time-series sensor data analysis. A quick introduction about time-series data is also provided.
Data Analysis, Python, Sensors, Time Series
Approaching (Almost) Any Machine Learning Problem - Feb 18, 2021.
This freely-available book is a fantastic walkthrough of practical approaches to machine learning problems.
Deep Learning, Free ebook, Machine Learning, Python
- Distributed and Scalable Machine Learning [Webinar] - Feb 17, 2021.
Mike McCarty and Gil Forsyth work at the Capital One Center for Machine Learning, where they are building internal PyData libraries that scale with Dask and RAPIDS. For this webinar, Feb 23 @ 2 pm PST, 5pm EST, they’ll join Hugo Bowne-Anderson and Matthew Rocklin to discuss their journey to scale data science and machine learning in Python.
Capital One, Dask, Distributed, Machine Learning, Python, scikit-learn, XGBoost
- 10 resources for data science self-study - Feb 17, 2021.
Many resources exist for the self-study of data science. In our modern age of information technology, an enormous amount of free learning resources are available to anyone, and with effort and dedication, you can master the fundamentals of data science.
Data Science, Data Science Certificate, Data Science Education, Kaggle, MOOC, Python, Youtube
- Easy, Open-Source AutoML in Python with EvalML - Feb 16, 2021.
We’re excited to announce that a new open-source project has joined the Alteryx open-source ecosystem. EvalML is a library for automated machine learning (AutoML) and model understanding, written in Python.
Automated Machine Learning, AutoML, Machine Learning, Open Source, Python
- How to Speed up Scikit-Learn Model Training - Feb 11, 2021.
Scikit-Learn is an easy to use a Python library for machine learning. However, sometimes scikit-learn models can take a long time to train. The question becomes, how do you create the best scikit-learn model in the least amount of time?
Distributed Systems, Hyperparameter, Machine Learning, Optimization, Parallelism, Python, scikit-learn, Training
- 7 Most Recommended Skills to Learn to be a Data Scientist - Feb 10, 2021.
The Data Scientist professional has emerged as a true interdisciplinary role that spans a variety of skills, theoretical and practical. For the core, day-to-day activities, many critical requirements that enable the delivery of real business value reach well outside the realm of machine learning, and should be mastered by those aspiring to the field.
Career Advice, Data Science Skills, Data Scientist, Data Visualization, Docker, Pandas, Python, SQL
- How to Deploy a Flask API in Kubernetes and Connect it with Other Micro-services - Feb 9, 2021.
A hands-on tutorial on how to implement your micro-service architecture using the powerful container orchestration tool Kubernetes.
API, Containers, Flask, Kubernetes, MySQL, Python, SQL
- Essential Math for Data Science: Introduction to Matrices and the Matrix Product - Feb 5, 2021.
As vectors, matrices are data structures allowing you to organize numbers. They are square or rectangular arrays containing values organized in two dimensions: as rows and columns. You can think of them as a spreadsheet. Learn more here.
Data Science, Linear Algebra, Mathematics, numpy, Python
- Build Your First Data Science Application - Feb 4, 2021.
Check out these seven Python libraries to make your first data science MVP application.
API, Data Science, Jupyter, Keras, numpy, Pandas, Plotly, Python, PyTorch, scikit-learn
How to create stunning visualizations using python from scratch - Feb 4, 2021.
Data science and data analytics can be beautiful things. Not only because of the insights and enhancements to decision-making they can provide, but because of the rich visualizations about the data that can be created. Following this step-by-step guide using the Matplotlib and Seaborn libraries will help you improve the presentation and effective communication of your work.
Data Visualization, Matplotlib, Python, Seaborn
- Getting Started with 5 Essential Natural Language Processing Libraries - Feb 3, 2021.
This article is an overview of how to get started with 5 popular Python NLP libraries, from those for linguistic data visualization, to data preprocessing, to multi-task functionality, to state of the art language modeling, and beyond.
Data Preparation, Data Preprocessing, Data Visualization, Hugging Face, NLP, Python, spaCy, Text Analytics, Transformer
- Working With The Lambda Layer in Keras - Jan 28, 2021.
In this tutorial we'll cover how to use the Lambda layer in Keras to build, save, and load models which perform custom operations on your data.
Architecture, Keras, Neural Networks, Python
- Mastering TensorFlow Variables in 5 Easy Steps - Jan 20, 2021.
Learn how to use TensorFlow Variables, their differences from plain Tensor objects, and when they are preferred over these Tensor objects | Deep Learning with TensorFlow 2.x.
Neural Networks, Python, TensorFlow
- Comprehensive Guide to the Normal Distribution - Jan 18, 2021.
Drop in for some tips on how this fundamental statistics concept can improve your data science.
Distribution, Normal Distribution, Python, SciPy, Statistics
Cleaner Data Analysis with Pandas Using Pipes - Jan 15, 2021.
Check out this practical guide on Pandas pipes.
Data Analysis, Data Cleaning, Pandas, Pipeline, Python
- Creating Good Meaningful Plots: Some Principles - Jan 12, 2021.
Hera are some thought starters to help you create meaningful plots.
Charts, Data Visualization, Python, R
- 5 Tools for Effortless Data Science - Jan 11, 2021.
The sixth tool is coffee.
Data Science, Data Science Tools, Keras, Machine Learning, MLflow, PyCaret, Python
Best Python IDEs and Code Editors You Should Know - Jan 8, 2021.
Developing machine learning algorithms requires implementing countless libraries and integrating many supporting tools and software packages. All this magic must be written by you in yet another tool -- the IDE -- that is fundamental to all your code work and can drive your productivity. These top Python IDEs and code editors are among the best tools available for you to consider, and are reviewed with their noteworthy features.
IDE, Jupyter, PyCharm, Python, Visual Studio Code
10 Underappreciated Python Packages for Machine Learning Practitioners - Jan 7, 2021.
Here are 10 underappreciated Python packages covering neural architecture design, calibration, UI creation and dissemination.
Deployment, Neural Networks, Python, UI/UX
15 Free Data Science, Machine Learning & Statistics eBooks for 2021 - Dec 31, 2020.
We present a curated list of 15 free eBooks compiled in a single location to close out the year.
Automated Machine Learning, Data Science, Deep Learning, Free ebook, Machine Learning, NLP, Python, R, Statistics
Generating Beautiful Neural Network Visualizations - Dec 30, 2020.
If you are looking to easily generate visualizations of neural network architectures, PlotNeuralNet is a project you should check out.
Neural Networks, Python, Visualization
- Monte Carlo integration in Python - Dec 24, 2020.
A famous Casino-inspired trick for data science, statistics, and all of science. How to do it in Python?
Monte Carlo, Python, Simulation, Statistics
- Production Machine Learning Monitoring: Outliers, Drift, Explainers & Statistical Performance - Dec 21, 2020.
A practical deep dive on production monitoring architectures for machine learning at scale using real-time metrics, outlier detectors, drift detectors, metrics servers and explainers.
AI, Deployment, Explainable AI, Machine Learning, Modeling, Outliers, Production, Python
- Fast and Intuitive Statistical Modeling with Pomegranate - Dec 21, 2020.
Pomegranate is a delicious fruit. It can also be a super useful Python library for statistical analysis. We will show how in this article.
Distribution, Markov Chains, Probability, Python, Statistical Modeling
- How to use Machine Learning for Anomaly Detection and Conditional Monitoring - Dec 16, 2020.
This article explains the goals of anomaly detection and outlines the approaches used to solve specific use cases for anomaly detection and condition monitoring.
Anomaly Detection, Machine Learning, Python, scikit-learn, Unsupervised Learning
- Data Science and Machine Learning: The Free eBook - Dec 15, 2020.
Check out the newest addition to our free eBook collection, Data Science and Machine Learning: Mathematical and Statistical Methods, and start building your statistical learning foundation today.
Data Science, Free ebook, Machine Learning, Python
- How to Create Custom Real-time Plots in Deep Learning - Dec 14, 2020.
How to generate real-time visualizations of custom metrics while training a deep learning model using Keras callbacks.
Data Visualization, Deep Learning, Keras, Metrics, Neural Networks, Python
- Matrix Decomposition Decoded - Dec 11, 2020.
This article covers matrix decomposition, as well as the underlying concepts of eigenvalues (lambdas) and eigenvectors, as well as discusses the purpose behind using matrix and vectors in linear algebra.
Linear Algebra, Mathematics, numpy, PCA, Python
- A Rising Library Beating Pandas in Performance - Dec 11, 2020.
This article compares the performance of the well-known pandas library with pypolars, a rising DataFrame library written in Rust. See how they compare.
Data Processing, Pandas, Performance, Python
- 10 Python Skills They Don’t Teach in Bootcamp - Dec 11, 2020.
Ascend to new heights in Data Science and Machine Learning with this thrilling list of coding tips.
Bootcamp, Programming, Python
- Implementing the AdaBoost Algorithm From Scratch - Dec 10, 2020.
AdaBoost technique follows a decision tree model with a depth equal to one. AdaBoost is nothing but the forest of stumps rather than trees. AdaBoost works by putting more weight on difficult to classify instances and less on those already handled well. AdaBoost algorithm is developed to solve both classification and regression problem. Learn to build the algorithm from scratch here.
Adaboost, Algorithms, Ensemble Methods, Machine Learning, Python
- Data Compression via Dimensionality Reduction: 3 Main Methods - Dec 10, 2020.
Lift the curse of dimensionality by mastering the application of three important techniques that will help you reduce the dimensionality of your data, even if it is not linearly separable.
Compression, Dimensionality Reduction, LDA, PCA, Python
R or Python? Why Not Both? - Dec 9, 2020.
Do you use both R and Python, either in different projects or in the same? Check out prython, an IDE designed to handle your needs.
Data Analysis, Data Science, IDE, Programming, Python, R
- Merging Pandas DataFrames in Python - Dec 8, 2020.
A quick how-to guide for merging Pandas DataFrames in Python.
Data Preparation, Data Preprocessing, Data Processing, Pandas, Python
- Change the Background of Any Video with 5 Lines of Code - Dec 7, 2020.
Learn to blur, color, grayscale and create a virtual background for a video with PixelLib.
Computer Vision, Image Processing, Machine Learning, Python, Segmentation, Video
- Pruning Machine Learning Models in TensorFlow - Dec 4, 2020.
Read this overview to learn how to make your models smaller via pruning.
Machine Learning, Modeling, Python, TensorFlow
- 10 Python Skills for Beginners - Dec 3, 2020.
Python is the fastest growing, most-beloved programming language. Get started with these Data Science tips.
Data Science, Programming, Python, Tips
- Object-Oriented Programming Explained Simply for Data Scientists - Dec 1, 2020.
Read this simple but effective guide to start using Classes in Python 3.
Data Science, Data Scientist, Explained, Programming, Python
- Deploying Trained Models to Production with TensorFlow Serving - Nov 30, 2020.
TensorFlow provides a way to move a trained model to a production environment for deployment with minimal effort. In this article, we’ll use a pre-trained model, save it, and serve it using TensorFlow Serving.
Deployment, Modeling, Neural Networks, Python, TensorFlow
- Data Science History and Overview - Nov 30, 2020.
In this era of big data that is only getting bigger, a huge amount of information from different fields is gathered and stored. Its analysis and extraction of value have become one of the most attractive tasks for companies and society in general, which is harnessed by the new professional role of the Data Scientist.
About Gregory Piatetsky, Data Science, Data Scientist, History, Python
- Essential Math for Data Science: Integrals And Area Under The Curve - Nov 25, 2020.
In this article, you’ll learn about integrals and the area under the curve using the practical data science example of the area under the ROC curve used to compare the performances of two machine learning models.
Machine Learning, Mathematics, Metrics, numpy, Python, Unbalanced
- How to Incorporate Tabular Data with HuggingFace Transformers - Nov 25, 2020.
In real-world scenarios, we often encounter data that includes text and tabular features. Leveraging the latest advances for transformers, effectively handling situations with both data structures can increase performance in your models.
Data Preparation, Deep Learning, Machine Learning, NLP, Python, Transformer
- Simple Python Package for Comparing, Plotting & Evaluating Regression Models - Nov 25, 2020.
This package is aimed to help users plot the evaluation metric graph with single line code for different widely used regression model metrics comparing them at a glance. With this utility package, it also significantly lowers the barrier for the practitioners to evaluate the different machine learning algorithms in an amateur fashion by applying it to their everyday predictive regression problems.
Data Visualization, Metrics, Modeling, Python, Regression
TabPy: Combining Python and Tableau - Nov 24, 2020.
This article demonstrates how to get started using Python in Tableau.
Data Visualization, Python, Tableau
- Computer Vision at Scale With Dask And PyTorch - Nov 23, 2020.
A tutorial on conducting image classification inference using the Resnet50 deep learning model at scale with using GPU clusters on Saturn Cloud. The results were: 40x faster computer vision that made a 3+ hour PyTorch model run in just 5 minutes.
Computer Vision, Dask, Python, PyTorch, Scalability
- Top 6 Data Science Programs for Beginners - Nov 20, 2020.
Udacity has the best industry-leading programs in data science. Here are the top six data science courses for beginners to help you get started.
Beginners, Certificate, Data Engineer, Data Science Education, Data Visualization, Online Education, Python, R, SQL, Udacity
- Algorithms for Advanced Hyper-Parameter Optimization/Tuning - Nov 17, 2020.
In informed search, each iteration learns from the last, whereas in Grid and Random, modelling is all done at once and then the best is picked. In case for small datasets, GridSearch or RandomSearch would be fast and sufficient. AutoML approaches provide a neat solution to properly select the required hyperparameters that improve the model’s performance.
Automated Machine Learning, AutoML, Hyperparameter, Optimization, Python
- 5 Things You Are Doing Wrong in PyCaret - Nov 16, 2020.
PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few words only. This makes experiments exponentially fast and efficient. Find out 5 ways to improve your usage of the library.
Machine Learning, PyCaret, Python, Tips
Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision - Nov 16, 2020.
This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.
Computer Vision, Data Science, Deep Learning, Machine Learning, Neural Networks, NLP, Python
- tensorflow + dalex = :) , or how to explain a TensorFlow model - Nov 13, 2020.
Having a machine learning model that generates interesting predictions is one thing. Understanding why it makes these predictions is another. For a tensorflow predictive model, it can be straightforward and convenient develop an explainable AI by leveraging the dalex Python package.
Dalex, Explainability, Explainable AI, Machine Learning, Python, TensorFlow
- Learn to build an end to end data science project - Nov 11, 2020.
Appreciating the process you must work through for any Data Science project is valuable before you land your first job in this field. With a well-honed strategy, such as the one outlined in this example project, you will remain productive and consistently deliver valuable machine learning models.
Data Preparation, Data Science, GitHub, Portfolio, Python, Regression, Salary
- Mastering TensorFlow Tensors in 5 Easy Steps - Nov 11, 2020.
Discover how the building blocks of TensorFlow works at the lower level and learn how to make the most of Tensor objects.
Deep Learning, Python, Tensor, TensorFlow
Every Complex DataFrame Manipulation, Explained & Visualized Intuitively - Nov 10, 2020.
Most Data Scientists might hail the power of Pandas for data preparation, but many may not be capable of leveraging all that power. Manipulating data frames can quickly become a complex task, so eight of these techniques within Pandas are presented with an explanation, visualization, code, and tricks to remember how to do it.
Data Preparation, Pandas, Python
- Change the Background of Any Image with 5 Lines of Code - Nov 9, 2020.
Blur, color, grayscale and change the background of any image with a picture using PixelLib.
Computer Vision, Image Processing, Machine Learning, Python, Segmentation
- Pandas on Steroids: End to End Data Science in Python with Dask - Nov 6, 2020.
End to end parallelized data science from reading big data to data manipulation to visualisation to machine learning.
Dask, Data Science, Pandas, Python
- How to Build a Football Dataset with Web Scraping - Nov 5, 2020.
This article covers using Selenium to scrape JavaScript rendered content.
Javascript, Python, Selenium, Soccer, Web Scraping
- How to deploy PyTorch Lightning models to production - Nov 5, 2020.
A complete guide to serving PyTorch Lightning models at scale.
Deployment, Neural Networks, Production, Python, PyTorch, PyTorch Lightning
- KDnuggets™ News 20:n42, Nov 4: Top Python Libraries for Data Science, Data Visualization & Machine Learning; Mastering Time Series Analysis - Nov 4, 2020.
Top Python Libraries for Data Science, Data Visualization, Machine Learning; Mastering Time Series Analysis with Help From the Experts; Explaining the Explainable AI: A 2-Stage Approach; The Missing Teams For Data Scientists; and more.
Career Advice, Data Science Team, Explainable AI, Python, Time Series
- Building Deep Learning Projects with fastai — From Model Training to Deployment - Nov 4, 2020.
A getting started guide to develop computer vision application with fastai.
Deep Learning, Deployment, fast.ai, Modeling, Python, Training
Building Neural Networks with PyTorch in Google Colab - Oct 30, 2020.
Combining PyTorch and Google's cloud-based Colab notebook environment can be a good solution for building neural networks with free access to GPUs. This article demonstrates how to do just that.
Deep Learning, Google Colab, Neural Networks, Python, PyTorch
- Dealing with Imbalanced Data in Machine Learning - Oct 29, 2020.
This article presents tools & techniques for handling data when it's imbalanced.
Balancing Classes, Machine Learning, Python
- Stop Running Jupyter Notebooks From Your Command Line - Oct 28, 2020.
Instead, run your Jupyter Notebook as a stand alone web app.
App, Data Science, Docker, Jupyter, Python
- Which flavor of BERT should you use for your QA task? - Oct 22, 2020.
Check out this guide to choosing and benchmarking BERT models for question answering.
BERT, NLP, Python, Question answering
- 10 Underrated Python Skills - Oct 21, 2020.
Tips for feature analysis, hyperparameter tuning, data visualization and more.
Data Analysis, Data Science Skills, Data Visualization, MLflow, Pandas, Programming, Python, Time Series
- Deploying Streamlit Apps Using Streamlit Sharing - Oct 20, 2020.
Read this sneak peek into Streamlit’s new deployment platform.
Deployment, Python, Streamlit
- Data Science in the Cloud with Dask - Oct 20, 2020.
Scaling large data analyses for data science and machine learning is growing in importance. Dask and Coiled are making it easy and fast for folks to do just that. Read on to find out how.
Cloud, Dask, Data Science, Python
- Feature Ranking with Recursive Feature Elimination in Scikit-Learn - Oct 19, 2020.
This article covers using scikit-learn to obtain the optimal number of features for your machine learning project.
Feature Selection, Machine Learning, Python, scikit-learn
- Roadmap to Natural Language Processing (NLP) - Oct 19, 2020.
Check out this introduction to some of the most common techniques and models used in Natural Language Processing (NLP).
Data Preprocessing, LDA, NLP, Python, Roadmap, Sentiment Analysis, Transformer, Word Embeddings
- Fast Gradient Boosting with CatBoost - Oct 16, 2020.
In this piece, we’ll take a closer look at a gradient boosting library called CatBoost.
CatBoost, Gradient Boosting, Machine Learning, Python
fastcore: An Underrated Python Library - Oct 15, 2020.
A unique python library that extends the python programming language and provides utilities that enhance productivity.
Development, fast.ai, Programming, Python
Free From MIT: Intro to Computational Thinking and Data Science - Oct 14, 2020.
This free course from MIT will help in your transition to thinking computationally, and ultimately solving complex data science problems.
Computer Science, Courses, Data Science, MIT, Python
- Getting Started with PyTorch - Oct 14, 2020.
A practical walkthrough on how to use PyTorch for data analysis and inference.
Neural Networks, Python, PyTorch
- Exploring The Brute Force K-Nearest Neighbors Algorithm - Oct 12, 2020.
This article discusses a simple approach to increasing the accuracy of k-nearest neighbors models in a particular subset of cases.
Algorithms, K-nearest neighbors, Machine Learning, Python
- Here are the Most Popular Python IDEs/Editors - Oct 6, 2020.
Jupyter Notebook continues to lead as the most popular Python IDE, but its share has declined since the last poll. The top 4 contenders have remained the same, but only one has significantly improved its share. We also examine the breakdown by employment and region.
IDE, Jupyter, Poll, PyCharm, Python, Visual Studio Code
- 10 Best Machine Learning Courses in 2020 - Oct 6, 2020.
If you are ready to take your career in machine learning to the next level, then these top 10 Machine Learning Courses covering both practical and theoretical work will help you excel.
Courses, DataCamp, Deep Learning, fast.ai, Machine Learning, Online Education, Python, Stanford
- Your Guide to Linear Regression Models - Oct 5, 2020.
This article explains linear regression and how to program linear regression models in Python.
Linear Regression, Python
- Key Machine Learning Technique: Nested Cross-Validation, Why and How, with Python code - Oct 5, 2020.
Selecting the best performing machine learning model with optimal hyperparameters can sometimes still end up with a poorer performance once in production. This phenomenon might be the result of tuning the model and evaluating its performance on the same sets of train and test data. So, validating your model more rigorously can be key to a successful outcome.
Cross-validation, Machine Learning, Python
- KDnuggets™ News 20:n37, Sep 30: Introduction to Time Series Analysis in Python; How To Improve Machine Learning Model Accuracy - Sep 30, 2020.
Learn how to work with time series in Python; Tips for improving Machine Learning model accuracy from 80% to over 90%; Geographical Plots with Python; Best methods for making Python programs blazingly fast; Read a complete guide to PyTorch; KDD Best Paper Awards and more.
Accuracy, Geospatial, KDD, Performance, Python, PyTorch, Time Series
- Looking Inside The Blackbox: How To Trick A Neural Network - Sep 28, 2020.
In this tutorial, I’ll show you how to use gradient ascent to figure out how to misclassify an input.
Neural Networks, Python, PyTorch, PyTorch Lightning
Geographical Plots with Python - Sep 28, 2020.
When your data includes geographical information, rich map visualizations can offer significant value for you to understand your data and for the end user when interpreting analytical results.
Choropleth, Data Visualization, Geospatial, Plotly, Python
- Making Python Programs Blazingly Fast - Sep 25, 2020.
Let’s look at the performance of our Python programs and see how to make them up to 30% faster!
Development, Optimization, Programming, Python
- Create and Deploy your First Flask App using Python and Heroku - Sep 25, 2020.
Flask is a straightforward and lightweight web application framework for Python applications. This guide walks you through how to write an application using Flask with a deployment on Heroku.
App, Deployment, Flask, Heroku, Python
Introduction to Time Series Analysis in Python - Sep 24, 2020.
Data that is updated in real-time requires additional handling and special care to prepare it for machine learning models. The important Python library, Pandas, can be used for most of this work, and this tutorial guides you through this process for analyzing time-series data.
Pandas, Python, time, Time Series
- The Most Complete Guide to PyTorch for Data Scientists - Sep 24, 2020.
All the PyTorch functionality you will ever need while doing Deep Learning. From an Experimentation/Research Perspective.
Data Science, Data Scientist, Neural Networks, Python, PyTorch
